metadata
tags:
- stable-diffusion-xl
- stable-diffusion-xl-diffusers
- diffusers-training
- text-to-image
- diffusers
- lora
- template:sd-lora
widget:
- text: a <s0><s1> emoji dressed as yoda
output:
url: image_0.png
- text: a <s0><s1> emoji dressed as yoda
output:
url: image_1.png
- text: a <s0><s1> emoji dressed as yoda
output:
url: image_2.png
- text: a <s0><s1> emoji dressed as yoda
output:
url: image_3.png
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: a <s0><s1> emoji
license: openrail++
SDXL LoRA DreamBooth - linoyts/huggy_edm_lora_v4
![](https://huggingface.co/linoyts/huggy_edm_lora_v4/resolve/main/image_0.png)
- Prompt
- a <s0><s1> emoji dressed as yoda
![](https://huggingface.co/linoyts/huggy_edm_lora_v4/resolve/main/image_1.png)
- Prompt
- a <s0><s1> emoji dressed as yoda
![](https://huggingface.co/linoyts/huggy_edm_lora_v4/resolve/main/image_2.png)
- Prompt
- a <s0><s1> emoji dressed as yoda
![](https://huggingface.co/linoyts/huggy_edm_lora_v4/resolve/main/image_3.png)
- Prompt
- a <s0><s1> emoji dressed as yoda
Model description
These are linoyts/huggy_edm_lora_v4 LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
Download model
Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
- LoRA: download
huggy_edm_lora_v4.safetensors
here 💾.- Place it on your
models/Lora
folder. - On AUTOMATIC1111, load the LoRA by adding
<lora:huggy_edm_lora_v4:1>
to your prompt. On ComfyUI just load it as a regular LoRA.
- Place it on your
- Embeddings: download
huggy_edm_lora_v4_emb.safetensors
here 💾.- Place it on it on your
embeddings
folder - Use it by adding
huggy_edm_lora_v4_emb
to your prompt. For example,a huggy_edm_lora_v4_emb emoji
(you need both the LoRA and the embeddings as they were trained together for this LoRA)
- Place it on it on your
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
from huggingface_hub import hf_hub_download
from safetensors.torch import load_file
pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('linoyts/huggy_edm_lora_v4', weight_name='pytorch_lora_weights.safetensors')
embedding_path = hf_hub_download(repo_id='linoyts/huggy_edm_lora_v4', filename='huggy_edm_lora_v4_emb.safetensors', repo_type="model")
state_dict = load_file(embedding_path)
pipeline.load_textual_inversion(state_dict["clip_l"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder, tokenizer=pipeline.tokenizer)
pipeline.load_textual_inversion(state_dict["clip_g"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder_2, tokenizer=pipeline.tokenizer_2)
image = pipeline('a <s0><s1> emoji dressed as yoda').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
Trigger words
To trigger image generation of trained concept(or concepts) replace each concept identifier in you prompt with the new inserted tokens:
to trigger concept TOK
→ use <s0><s1>
in your prompt
Details
All Files & versions.
The weights were trained using 🧨 diffusers Advanced Dreambooth Training Script.
LoRA for the text encoder was enabled. False.
Pivotal tuning was enabled: True.
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.